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About the Team:
As part of the Search, Recommendation, Ads (Engineering & Architecture) team, We build and operate the search engine that powers retrieval and ranking across the company. The system is built on Vespa (a 1.7M-line C++/Java codebase) and runs at scale across hundreds of nodes. Our work spans the full stack: cluster orchestration, HNSW-based vector indexing, rank expression evaluation, capacity planning, and the developer tooling that keeps all of it shippable. We care a lot about correctness, latency tails, and operational simplicity.
Job Description:
Design, implement, and operate components of the search engine - indexing, query execution, ranking, or storage using C++
Improve indexing and retrieval performance: SIMD-friendly data layouts, cache-aware algorithms, lock contention
Extend vector search capabilities (HNSW and beyond) and integrate them cleanly with traditional inverted-index retrieval
Build tooling and automation that makes the team faster - capacity models, fault-injection tests, deployment checks, AI-assisted workflows
Participate in design reviews, code reviews, and on-call rotation
Job Requirements:
Bachelor's Degree or higher in Computer Science
At least 5 years of full time backend development experience using C++
Experience working on a search engine, database, or storage system such as Vespa is preferred
Familiarity with vector search and ANN algorithms (HNSW, IVF, PQ).
Solid foundation in data structures, algorithms, and systems. You can reason about cache behavior, memory layout, and concurrency..
Experience operating non-trivial services in production: profiling, debugging core dumps, reading flamegraphs, tracing distributed requests.
Comfortable working in a large existing codebase.
Strong written communication. You write design docs and PR descriptions that the next on-call can actually use.
Job ID: 148298023
Skills:
Algorithms, Java, Debugging, data structures, deployment checks, vector search, tracing, AI-assisted workflows, lock contention, capacity models, HNSW, flamegraphs, cache-aware algorithms, Systems, Profiling, SIMD-friendly data layouts, fault-injection tests, distributed requests, ANN algorithms, Vespa, core dumps
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